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OLP 기반 이벤트/사이클 혼합 방식 산업용 로봇 시뮬레이션 엔진 구현
한정욱(Jungwook Han),류기열(Kiyeol Ryu),이정태(Jungtae Lee),범진환(Jinhwan Borm),김종철(Jongchul Kim),김재욱(Jaewook Kim) 한국정보과학회 2006 한국정보과학회 학술발표논문집 Vol.33 No.1
산업현장에서 로봇의 사용이 크게 늘게 됨으로서 로봇의 배치와 움직임의 조정을 효율적으로 하는 것이 중요해 졌다. 이를 위해 가상의 공간에서 시뮬레이션 하는 오프라인 프로그래밍이 사용되고 있다. 본 논문에서는 오프라인 프로그래밍 기반의 시뮬레이션 엔진을 설계, 구현하였다. 복수의 로봇 시뮬레이션이 정적/동적인 상황에서 이루어 질 수 있도록 이벤트/사이클 혼합 방식을 사용 하였다.
분할 선형 회귀모형을 이용한 여단급 KCTC 방어작전간 보병대대 전투승리 영향요소 분석
한정욱(Jungwook Han),이민호(Minho Lee),박진영(Jinyoung Park),문호석(Hoseok Moon) 육군사관학교 화랑대연구소 2021 한국군사학논집 Vol.77 No.2
This study is on combat victory influence factors of infantry battalion during brigade-level KCTC(Korea combat training center) defensive operations in ROKA(republic of Korea army). For this study, we analyzed brigade-level KCTC training results accumulated from 2018. Most previous studies on KCTC training results have analyzed individual combatants using battalion-level KCTC training results that have been ended in 2012. But in this study, we used brigade-level KCTC training results and evaluated victory factors of units such as infantry battalion. For scientific analysis on KCTC training results, we have used brigade-level KCTC training data, AAR(after action review), and military doctrine. Specifically, we utilized tactical knowledge and scientific methodology for the quantitative definition of response and predictor variables. The infantry battalion"s combat victory influence factors were analyzed during the defensive operations using segmented linear regression analysis through the definition of variables. The results of this study provide insight into what factors are important to victory during defensive operations. We expect the results of this study will contribute not only to the operations of infantry battalion combat power but also to the scientific analysis of brigade-level KCTC training big data.
GPS 사용 제한 조건에서의 무인선 레이다를 활용한 연안항법
한정욱(Jungwook Han),김진환(Jinwhan Kim),손남선(Nam-sun Son) 제어로봇시스템학회 2018 제어·로봇·시스템학회 논문지 Vol.24 No.8
Global positioning system (GPS) is an important navigational device for field operations with unmanned surface vehicles (USVs) in marine environments. However, the use of GPS may not be available in some situations because GPS signals can be easily blocked by large surrounding structures and are vulnerable to natural interference and intentional jamming attacks. This study proposes an alternative navigation approach for USV operation with an onboard marine radar when the use of GPS is restricted and prohibited. Marine radar is a standard navigational sensor for a marine vehicle that can be utilized for vehicle localization in coastal areas. The surrounding coastlines can be extracted from radar measurements and the vehicle’s position can be estimated by matching the obtained coastline features with a pre-built map. The performance of the proposed navigation method was assessed by a field experiment in a real coastal environment. The results are presented and discussed in this paper.
무인수상선의 자율운항을 위한 단안 카메라 기반의 근거리 선박 자동 탐지
박정홍(Jeonghong Park),한정욱(Jungwook Han),김진환(Jinwhan Kim),손남선(Nam-sun Son),김선영(Sun Young Kim) 제어로봇시스템학회 2017 제어·로봇·시스템학회 논문지 Vol.23 No.6
Automatic detection and tracking of nearby ships are important capabilities for the autonomous operation of unmanned surface vehicles (USVs). This study focuses on achieving such capabilities in the framework of vision-based perception and sensor fusion. Reliable detection and tracking processes using a monocular camera are designed to automatically detect maneuvering targets with no prior information on the motion of targets. For a reliable trajectory estimation in low observability situations, the proposed vision-based approach uses bearing information in both the horizontal and vertical directions. In addition, the measurement by an onboard lidar is integrated into the vision-based tracking filter when the targets are in close range. The performance of the proposed method was assessed by field experiment data obtained in a real-sea environment to show the feasibility of the developed algorithms for the autonomous navigation of USVs.
해양환경에서 선박 추적을 위한 라이다를 이용한 궤적 초기화 및 표적 추적 필터
황태현(Tae Hyun Fang),한정욱(Jungwook Han),손남선(Nam-Sun Son),김선영(Sun Young Kim) 제어로봇시스템학회 2016 제어·로봇·시스템학회 논문지 Vol.22 No.2
This paper describes the track initiation and target-tracking filter for ship tracking in a marine environment by using Light Detection And Ranging (LiDAR). LiDAR with three-dimensional scanning capability is more useful for target tracking in the short to medium range compared to RADAR. LiDAR has rotating multi-beams that return point clouds reflected from targets. Through preprocessing the cluster of the point cloud, the center point can be obtained from the cloud. Target tracking is carried out by using the center points of targets. The track of the target is initiated by investigating the normalized distance between the center points and connecting the points. The regular track obtained from the track initiation can be maintained by the target-tracking filter, which is commonly used in radar target tracking. The target-tracking filter is constructed to track a maneuvering target in a cluttered environment. The target-tracking algorithm including track initiation is experimentally evaluated in a sea-trial test with several boats.
여단급 KCTC 훈련결과 빅데이터를 활용한 전투승리요인 분석 방법론 연구 : 보병대대 공격작전 분석을 중심으로
이민호 ( Minho Lee ),한정욱 ( Jungwook Han ),박진영 ( Jinyoung Park ),문호석 ( Hoseok Moon ) 국방대학교 안보문제연구소 2021 국방연구 Vol.64 No.4
본 연구에서는 여단급 과학화전투(Korea Combat Training Center, KCTC) 훈련결과 빅데이터를 이용하여 전투승리요인을 분석하기 위한 방법론을 제안하였고, 보병대대 공격작전 시 전투승리요인을 분석하는 과정을 제시하였다. KCTC 훈련결과 데이터 분석과 관련된 기존 연구들은 연구의 대상이 주로 대대급 KCTC이었고, 분석 데이터도 훈련결과의 일부만 이용하였으며, 군사전문가의 전술적 평가가 연구에 반영되지 못했다는 제한점이 있었다. 본 연구에서는 이러한 기존 연구의 제한점을 극복하기 위해서 여단급 KCTC훈련 실시 후 2년간의 모든 훈련결과 데이터를 분석대상으로 하였고, 군사전문가의 평가를 훈련결과 분석에 반영하는 방법을 제안하였다. 군사전문가의 평가에 대한 분석은 교리와 KCTC 사후검토자료를 이용하였고, 이러한 분석을 술(術)적분석이라고 하였다. 술적분석은 훈련결과에 대한 과학적 분석 전에 선행되도록 하였고, 술적분석과 과학적분석을 결합하여 전투승패결과에 영향을 주는 전투승리요인을 제시하였다. KCTC 훈련결과 빅데이터를 이용하여 다양한 제대와 작전형태에 따른 훈련결과를 분석하는 데, 본 연구에서 제안하는 방법론이 군사전문가의 통찰력과 데이터에 의한 과학적 분석을 융합하여 훈련결과를 평가하는데 활용될 수 있을 것이다. This study proposed a methodology to analyze combat victory factors using big data as a result of the Korea Combat Training Center (KCTC) training and presented the case as analyzing combat victory factors during infantry battalion offensive operations. Existing studies related to KCTC training result data analysis mainly focused on the battalion-level KCTC, and the analysis data also used only a part of the training results, and there was a limitation that the tactical evaluation of military experts could not be reflected in the study. In this study, in order to overcome the limitations of the existing studies, all the training results data of the two years of the brigade-level KCTC training were analyzed as the subject of analysis, and a method of reflecting the evaluation of military experts in the analysis of the training results was proposed. For the analysis of the evaluation of military experts, the doctrine and the KCTC after action review data were used, and this analysis was called a tactical analysis. The tactical analysis was preceded by the scientific analysis of the training results, and the battle victory factors that affect the outcome of the battle were presented by combining the tactical analysis and scientific analysis. The methodology proposed in this study can be used to evaluate the training results in which the insights of military experts and scientific analysis based on data are fused to analyze the training results according to various types of troops and operations using KCTC training results big data.